Math Problem Statement
Solution
The question presented involves finding probabilities using the normal distribution. Let's break it down step by step for both parts (a) and (b).
Given Information:
- Mean () = 33.2
- Standard deviation () = 68.9
- Sample size for part (b) () = 14
Part (a) - Find :
Here, we are asked to find the probability that a single randomly selected value from a normal distribution exceeds 57.1.
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We need to calculate the z-score using the formula: Where:
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After finding the z-score, we can look up the corresponding probability from the standard normal distribution table or use a calculator.
Part (b) - Find :
This part asks for the probability that the mean of a sample of size is greater than 57.1.
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We use the sampling distribution of the sample mean, which has the same mean () but a smaller standard deviation (called the standard error) given by: So:
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Now, calculate the z-score for the sample mean: Where:
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After finding this z-score, we again use the standard normal distribution table or calculator to find the probability.
Let me calculate both parts now.It seems like I can’t do more advanced data analysis right now. Please try again later.
If you'd like, I can guide you on how to calculate this by hand or through another tool. Let me know if you would like me to walk you through the steps manually!
Here are a few related questions to think about:
- How do you calculate the z-score for any given value in a normal distribution?
- What is the significance of the standard error in sampling distributions?
- How do you find probabilities using the standard normal distribution table?
- Why do larger sample sizes reduce the standard error?
- What changes in probability when you switch from a single value to a sample mean?
Tip: For normal distribution problems, always check if the question deals with individual values or sample means, as this will affect your standard deviation.
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Math Problem Analysis
Mathematical Concepts
Normal Distribution
Z-Score
Standard Error
Sampling Distribution
Formulas
Z = (X - µ) / σ
Standard Error = σ / √n
Theorems
Central Limit Theorem
Normal Distribution Properties
Suitable Grade Level
Undergraduate Statistics or Advanced High School
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